Climate adaptation often requires high resolution information about the expected changes in the statistical distribution of user-relevant variables. Thanks to targeted national programmes, research projects and international climate service initiatives this kind of information is not only becoming more easily available but it is also making its way into building codes, engineering standards as well as the risk assessments for financial products. If such an increase in the use of climate data can be seen as a positive step towards the construction of a climate resilient society, it is also true that the inconsistencies that exist between the information derived from different sources of information, have the potential to reduce the user uptake, increase the costs of adaptation and even undermine the credibility of both climate services and the underpinning climate science.
This paper offers a personal reflection on the emerging user requirements in this field. The presenation also aims at suggesting some prelimimary ideas in support of the development of appropriate methodologies for extracting robust evidence from different sources in a scalable way.